Journal
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
Volume 29, Issue 17, Pages 25112-25137Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s11356-021-17609-w
Keywords
Homogenous regions; Trend analysis; Clustering; Mann-Kendall trend test; Sen's innovative trend analysis (ITA); Hierarchical clustering on principle component analysis (HCPC)
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Funding
- Deputyship for Research Innovation, Ministry of Education in Saudi Arabia [IFP-KKU-2020/13]
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Identifying homogeneous rainfall zones in Saudi Arabia is crucial for water resource and agriculture management. This study utilized various trend analysis techniques on 40-year rainfall records to identify three distinct clusters with different rainfall trends. The results will contribute to future work on climatic zone identification and water resource management strategies.
In Saudi Arabia, identifying homogenous zones based on rainfall patterns is critical for ensuring a predictable and stable water resource and agriculture management strategy. As a result, the present research aims to identify Saudi Arabia's homogeneous rainfall zones and examine rainfall patterns in these areas. By proposing a novel trend analysis technique with a particular graphical representation, this study utilises and compares the traditional Mann-Kendall (MK) test, modified MK test, and basic Sen-innovative trend analysis (ITA) method. Another approach is to use the Pettit change point test to objectively identify subcategories as low or high. The applications are based on 40-year rainfall records from 22 Saudi Arabian meteorological sites. K-means clustering and hierarchical clustering on principle component analysis (HCPC) were used to find homogeneous areas. The results of the homogeneous region identification revealed that the research area is divided into three clusters, each with three distinct climatic characteristics. Cluster 1 contains eight stations, whereas clusters 2 and 3 each have seven. The results of trend identification utilising the MK, MMK, and ITA tests revealed that cluster 1 had a falling rainfall trend, whereas cluster 2 had a very minor decreasing and increasing rainfall trend. Cluster 2 can be thought of as a transition zone. Cluster 3 observed an upward trend in rainfall. While the proposed new form of ITA produced similar results with more detailed analysis such as change point-based high and low value identification, and magnitude of decreasing and increasing trend, the proposed new form of ITA produced similar results with more detailed analysis such as change point-based high and low value identification. This study will serve as a foundation for future work by scientists and planners on the identification of climatic zones, the development of trend detection techniques, and the formulation of water resource management strategies.
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